Contraction Properties of the Advanced Step Real-Time Iteration for NMPC

Nurkanović, Armin; Zanelli, Andrea; Albrecht, Sebastian; Frison, Gianluca; Diehl, Moritz

doi:10.1016/j.ifacol.2020.12.449

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…Here, the optimal control problem might be solved in 2 kHz, but with variation of the control signal adapted to 10 kHz, see, e.g., [25]. Then, the interaction of open-and closed-loop control has to be taken into account [24], which might be addressed -if needed -by [7,20] or real-time iteration schemes in control [6] and estimation [26], see also the recently-proposed advanced step variants of the real-time iteration [18] (and [19] for an analysis of its convergence properties).…”

Section: Discussionmentioning

confidence: 99%

Model predictive control for retinal laser treatment at 1 kHz

Schaller¹,

Kleyman²,

Mordmüller³

et al. 2022

Preprint

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Laser photocoagulation is a technique applied in the treatment of retinal diseases. While this is often done manually or using simple control schemes, we pursue an optimization-based approach, namely Model Predictive Control (MPC), to enforce bounds on the peak temperature and, thus, safety during the medical treatment procedure -despite the spot-dependent absorption of the tissue. To this end, a repetition rate of 1 kHz is desirable rendering the real-time requirements a major challenge. We present a tailored MPC scheme using parametric model reduction, an extended Kalman filter for the parameter and state estimation, and suitably constructed stage costs and verify its applicability both in simulation and experiments with porcine eyes. Moreover, we give some insight on the implementation specifically tailored for fast numerical computations.

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Section: Discussionmentioning

confidence: 99%

Model predictive control for retinal laser treatment at 1 kHz

Schaller¹,

Kleyman²,

Mordmüller³

et al. 2022

Preprint

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acados—a modular open-source framework for fast embedded optimal control

et al. 2021

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Optimization-based primary and secondary control of microgrids

Nurkanović

Mešanović

Mario

et al. 2020

At - Automatisierungstechnik

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This article discusses how to use optimization-based methods to efficiently operate microgrids with a large share of renewables. We discuss how to apply a frequency-based method to tune the droop parameters in order to stabilize the grid and improve oscillation damping after disturbances. Moreover, we propose a centralized real-time feasible nonlinear model predictive control (NMPC) scheme to achieve efficient frequency and voltage control while considering economic dispatch results. Centralized NMPC for secondary control is a computationaly challenging task. We demonstrate how to reduce the computational burden using the Advanced Step Real-Time Iteration with nonuniform discretization grids. This reduces the computational burden up to 60 % compared to a standard uniform approach, while having only a minor performance loss. All methods are validated on the example of a 9-bus microgrid, which is modeled with a complex differential algebraic equation.

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Contraction Properties of the Advanced Step Real-Time Iteration for NMPC

Cited by 4 publications

References 15 publications

Model predictive control for retinal laser treatment at 1 kHz

Model predictive control for retinal laser treatment at 1 kHz

acados—a modular open-source framework for fast embedded optimal control

Optimization-based primary and secondary control of microgrids

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